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Human vs. machine: The impact of information processing on trading in OTC markets

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  • Box, Travis
  • Davis, Ryan

Abstract

This paper investigates the differential impact of human versus machine SEC filing downloads on trading activity in the OTC market. Human downloads drive immediate, significant increases in trading volume, especially for filings requiring qualitative interpretation, whereas machine downloads produce delayed and muted effects, mainly impacting standardized filings. These findings underscore the essential role of human interpretation in market responses and highlight the distinct effects of access modes on trading dynamics as OTC markets adapt to technological and regulatory shifts.

Suggested Citation

  • Box, Travis & Davis, Ryan, 2025. "Human vs. machine: The impact of information processing on trading in OTC markets," Finance Research Letters, Elsevier, vol. 72(C).
    • Handle: RePEc:eee:finlet:v:72:y:2025:i:c:s1544612324015459
    DOI: 10.1016/j.frl.2024.106516
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    References listed on IDEAS

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    1. Allaudeen Hameed & Randall Morck & Jianfeng Shen & Bernard Yeung, 2015. "Information, Analysts, and Stock Return Comovement," The Review of Financial Studies, Society for Financial Studies, vol. 28(11), pages 3153-3187.
    2. Michael A. Goldstein & Edith S. Hotchkiss & Erik R. Sirri, 2007. "Transparency and Liquidity: A Controlled Experiment on Corporate Bonds," The Review of Financial Studies, Society for Financial Studies, vol. 20(2), pages 235-273.
    3. Dyer, Travis & Lang, Mark & Stice-Lawrence, Lorien, 2017. "The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation," Journal of Accounting and Economics, Elsevier, vol. 64(2), pages 221-245.
    4. Cameron, A. Colin & Gelbach, Jonah B. & Miller, Douglas L., 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 238-249.
    5. Brian J. Bushee & Ian D. Gow & Daniel J. Taylor, 2018. "Linguistic Complexity in Firm Disclosures: Obfuscation or Information?," Journal of Accounting Research, Wiley Blackwell, vol. 56(1), pages 85-121, March.
    6. Gregory S. Miller & Douglas J. Skinner, 2015. "The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure," Journal of Accounting Research, Wiley Blackwell, vol. 53(2), pages 221-239, May.
    7. Travis Box & Danjue Shang, 2021. "Information‐driven stock price comovement," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(2), pages 403-429, June.
    8. Diamond, Douglas W & Verrecchia, Robert E, 1991. "Disclosure, Liquidity, and the Cost of Capital," Journal of Finance, American Finance Association, vol. 46(4), pages 1325-1359, September.
    9. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    10. Christian Leuz & Peter D. Wysocki, 2016. "The Economics of Disclosure and Financial Reporting Regulation: Evidence and Suggestions for Future Research," Journal of Accounting Research, Wiley Blackwell, vol. 54(2), pages 525-622, May.
    11. Bushee, Brian J. & Leuz, Christian, 2005. "Economic consequences of SEC disclosure regulation: evidence from the OTC bulletin board," Journal of Accounting and Economics, Elsevier, vol. 39(2), pages 233-264, June.
    12. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
    13. José María Liberti & Mitchell A Petersen, 2019. "Information: Hard and Soft," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 8(1), pages 1-41.
    14. Bushee, Brian J. & Matsumoto, Dawn A. & Miller, Gregory S., 2003. "Open versus closed conference calls: the determinants and effects of broadening access to disclosure," Journal of Accounting and Economics, Elsevier, vol. 34(1-3), pages 149-180, January.
    15. Tim Loughran & Bill McDonald, 2017. "The Use of EDGAR Filings by Investors," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(2), pages 231-248, April.
    16. Lee, Charles M.C. & Ma, Paul & Wang, Charles C.Y., 2015. "Search-based peer firms: Aggregating investor perceptions through internet co-searches," Journal of Financial Economics, Elsevier, vol. 116(2), pages 410-431.
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    More about this item

    Keywords

    SEC filings; Over-the-counter (OTC) securities; Public information; Automated trading; Information asymmetry;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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